Skill UI

A comprehensive guide for profiling, analyzing, and optimizing Python code. It addresses identifying performance bottlenecks related to CPU usage, excessive memory consumption, I/O operations, and slow data processing. Use this skill to improve application speed and efficiency in production environments.

A comprehensive skill set for building robust, type-safe, and highly performant Python 3.11+ applications. This specialist enforces best practices by generating type-annotated code, utilizing async/await patterns, structured dataclasses, and comprehensive error handling. The workflow mandates rigorous validation using tools like mypy (strict mode), black, ruff, and extensive pytest test suites to ensure code quality and reliability.

Automates PyTorch training workflows by guiding data preparation, model configuration, hyperparameter tuning, and experiment tracking while following industry best practices for production readiness.

Qdrant is a high-performance, Rust-powered vector database designed for production-grade RAG (Retrieval-Augmented Generation) and semantic search applications. It provides fast nearest neighbor search, supports complex hybrid search using metadata filtering, and offers horizontal scalability through sharding and replication. Ideal for building real-time recommendation systems and enterprise-level knowledge retrieval.

Automated quickstart guide generator that kicks in whenever you mention the trigger phrase, offering step-by-step technical documentation guidance, code samples, and validation to ensure API docs, user guides, and architecture notes stay production-ready.

Designs and implements production-grade RAG systems with document chunking, embeddings, vector stores, hybrid search, reranking, and evaluation, ideal for knowledge-grounded AI apps that need semantic retrieval, similarity search, and context augmentation.

Assists with automated guidance on rate limiter configuration as part of Security Fundamentals, offering best practices, production-ready snippets, and validation against standard security patterns whenever rate limiting questions arise.

Automates AWS RDS instance setups by providing prompts, best practices, and production-ready configs whenever you ask about RDS deployment procedures.

Automated assistance for building React components, offering best practices, production-ready code generation, and validation guidance for frontend patterns like accessibility and performance optimization.

Automates React Context setup within frontend development, guiding users through best practices, production-ready code, and validation for React-related modern web patterns.

A senior specialist for building modern, production-grade React applications using React 19, Server Components, and Next.js App Router. Expertise includes implementing complex state management (Redux, Zustand), optimizing performance with memoization, handling data fetching with TanStack Query, and ensuring strict TypeScript typing and accessibility standards. Ideal for architecting large-scale frontend systems.

A comprehensive architectural guide for building production-grade flowcharts using ReactFlow. This pattern set covers key challenges including hierarchical tree navigation (expandable/collapsible nodes), performance optimization via incremental rendering and memoization, and advanced state management using Redux-like reducer patterns with history tracking (undo/redo).